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Automated Detection of Cholesterol Presence using Iris Recognition Algorithm

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Sarika G. Songire, Madhuri S. Joshi
10.5120/ijca2016907867

Sarika G Songire and Madhuri S Joshi. Article: Automated Detection of Cholesterol Presence using Iris Recognition Algorithm. International Journal of Computer Applications 133(6):41-45, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Sarika G. Songire and Madhuri S. Joshi},
	title = {Article: Automated Detection of Cholesterol Presence using Iris Recognition Algorithm},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {6},
	pages = {41-45},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Arcus senilis is a grayish or whitish bow shaped or ring-shaped deposit in the cornea. It is associated with coronary heart disease (CHD). It is also recognized as a sign of hyperlipidemia. Iridology is an alternative medicine to detect diseases using iris’s pattern observation. Iridologists believe that the grayish or whitish deposit on the iris is sign of presence of cholesterol or Arcus senilis disease. The simple and non-invasive automation system is developed to detect cholesterol presence using iris recognition algorithm in image processing. This study applies iris recognition method to segment out the iris area, normalization process and lastly determines the cholesterol presence using OTSU’s thresholding method and histogram to determine the optimum threshold value. The result showed that the presence of cholesterol was high when the eigenvalue exceeds an optimum threshold value.

References

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Keywords

Biometric-Identification, Iris recognition, OTSU’s Algorithm, Arcus Senilis, Cholesterol Detection.